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Copy file name to clipboardExpand all lines: README.md
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*[Software article](https://doi.org/10.1186/s13321-018-0285-8) about P2Rank pocket prediction tool
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Krivak R, Hoksza D. ***P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure.*** Journal of Cheminformatics. 2018 Aug.
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*[A new web-server article](https://doi.org/10.1093/nar/gkac389) about updates in the web interface [prankweb.cz](https://prankweb.cz)
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*[Latest web-server article](https://doi.org/10.1093/nar/gkaf421) about updates in P2Rank and [prankweb.cz](https://prankweb.cz)
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Polak L, Skoda P, Riedlova K, Krivak R, Novotny M, Hoksza D. ***PrankWeb 4: a modular web server for protein–ligand binding site prediction and downstream analysis.*** Nucleic Acids Research, 2025 May.
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*[Web-server article](https://doi.org/10.1093/nar/gkac389) about updates in [prankweb.cz](https://prankweb.cz)
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Jakubec D, Skoda P, Krivak R, Novotny M, Hoksza D. ***PrankWeb 3: accelerated ligand-binding site predictions for experimental and modelled protein structures.*** Nucleic Acids Research, Volume 50, Issue W1, 5 July 2022, Pages W593–W597
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*[Web-server article](https://doi.org/10.1093/nar/gkz424) introducing the web interface at [prankweb.cz](https://prankweb.cz)
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*[Web-server article](https://doi.org/10.1093/nar/gkz424) introducing the web interface at [prankweb.cz](https://prankweb.cz)
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Jendele L, Krivak R, Skoda P, Novotny M, Hoksza D. ***PrankWeb: a web server for ligand binding site prediction and visualization.*** Nucleic Acids Research, Volume 47, Issue W1, 02 July 2019, Pages W345-W349
Krivak R, Hoksza D. ***P2RANK: Knowledge-Based Ligand Binding Site Prediction Using Aggregated Local Features.*** International Conference on Algorithms for Computational Biology 2015 Aug 4 (pp. 41-52). Springer
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~~~
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*[A new web-server article](https://doi.org/10.1093/nar/gkac389) about updates in the web interface [prankweb.cz](https://prankweb.cz)
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*[Latest web-server article](https://doi.org/10.1093/nar/gkaf421) about updates in P2Rank and [prankweb.cz](https://prankweb.cz)
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Polak L, Skoda P, Riedlova K, Krivak R, Novotny M, Hoksza D. ***PrankWeb 4: a modular web server for protein–ligand binding site prediction and downstream analysis.*** Nucleic Acids Research, 2025 May.
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~~~bibtex
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@article{prankweb4,
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author = {Polák, Lukáš and Škoda, Petr and Riedlová, Kamila and Krivák, Radoslav and Novotný, Marian and Hoksza, David},
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title = {PrankWeb 4: a modular web server for protein–ligand binding site prediction and downstream analysis},
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journal = {Nucleic Acids Research},
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pages = {gkaf421},
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year = {2025},
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month = {05},
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abstract = {Knowledge of protein–ligand binding sites (LBSs) is crucial for advancing our understanding of biology and developing practical applications in fields such as medicine or biotechnology. PrankWeb is a web server that allows users to predict LBSs from a given three-dimensional structure. It provides access to P2Rank, a state-of-the-art machine learning tool for binding site prediction. Here, we present a new version of PrankWeb enabling the development of both client- and server-side modules acting as postprocessing tasks on the predicted pockets. Furthermore, each module can be associated with a visualization module that acts on the results provided by both client- and server-side modules. This newly developed system was utilized to implement the ability to dock user-provided molecules into the predicted pockets using AutoDock Vina (server-side module) and to interactively visualize the predicted poses (visualization module). In addition to introducing a modular architecture, we revamped PrankWeb’s interface to better support the modules and enhance user interaction between the 1D and 3D viewers. We introduced a new, faster P2Rank backend or user-friendly exports, including ChimeraX visualization.},
*[Web-server article](https://doi.org/10.1093/nar/gkac389) about updates in the web interface [prankweb.cz](https://prankweb.cz)
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Jakubec D, Skoda P, Krivak R, Novotny M, Hoksza D. ***PrankWeb 3: accelerated ligand-binding site predictions for experimental and modelled protein structures.*** Nucleic Acids Research, Volume 50, Issue W1, 5 July 2022, Pages W593–W597
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